Reports

This country note presents the results of an analysis of Austria undertaken within the Labour Market Relevance and Outcomes of Higher Education Partnership Initiative project. The project was implemented by the OECD with the support of the European Commission with the aim of helping policy makers and higher education institutions enhance the employment outcomes of graduates by better aligning higher education provision and with current and emerging labour market skill demands. Austria is one of the few OECD countries where women comprise a smaller share of new entrants to Information and Communications Technology (ICT) master’s programmes than they do to bachelor’s degree programmes. This is especially a problem given the general preference of Austrian employers for master’s degrees over bachelor qualifications. Increasing the entry of women into ICT programmes, including postgraduate study, is a key government priority. Making progress requires both improvements to study guidance and support for students to raise success in their studies. The country note reviews the system context, highlights challenges faced by higher education institutions and, lessons learned from current practice, and presents policy options.

The economic shock induced by the COVID-19 pandemic is accelerating structural changes and is posing new challenges. Austria faces wider growth opportunities and new adjustment challenges related notably to two major structural transformations: transition to carbonless growth and the generalisation of more advanced forms of digitalisation. These imply new entries and exits in the business sector, more capital and labour re-allocations and greater geographic mobility of labour. A better activation of the existing talent pool, in particular female, elderly and migrant workers is also needed to address the ageing of the society. In this context public policies should aim at further stimulating business dynamism by facilitating market entries; supporting firms’ capacity to invest by helping strengthen their balance sheets; better adapting skills to jobs for all categories of workers; and providing the right incentives to R&D to boost long-term innovation.

Comprehensive and coordinated action across levels of government responsible for different policy domains (labour, education, housing and welfare/health) as well as across local actors is crucial to migrant integration. To respond to this need for co-ordination, different policy instruments are mobilised by countries. This paper presents six of them, to illustrate three categories of practices supporting migrant integration through better multi-level co-ordination: Reinforcing co-ordination (financial, human, technical) between levels of governments and private actors such as businesses or non-governmental organisations to foster migrant integration and retention: The Canadian Atlantic Immigration Pilot (AIP) and the French Territorial Contracts for the Reception and Integration of Refugees (CTAIR); Resolving information and evaluation asymmetries: Vienna (Austria) Integration and Diversity Monitor and the German Network IQ; Illustrating the positive externalities of territorial development and investment programmes on migrant integration and social cohesion: The Italian Inner Areas Strategy and the French Urban Policy.

A first step to implement effective migrant integration policies is to know who does what in policy sectors key to integration. Responding to this need, this paper offers policy makers a tool to understand the organisation of public action in key sectors for integration - Employment, Education, Housing, and Health/Welfare – in a sample of 10 OECD countries: Austria, Canada, France, Germany, Ireland, Italy, New Zealand, Spain, Sweden and the Netherlands. The complexity of the division of powers among levels of government calls for coordination mechanisms between actors, whatever the level of decentralisation. Besides, it throws lights on subnational governments’ role in integrating migrants and enabling them to participate to local development for the benefits of all. The geographic differences that exist in migrant presence and outcomes mean countries should build on local authorities' knowledge of local realities, aptitudes to coordinate different policy fields at the relevant scale and cooperate with non-governmental organisations.

Using a micro-level model of investment, this paper finds that firm-debt and investment are negatively associated across firms in Austrian manufacturing industries. The finding is robust to various changes to the model specification. Moreover, in an extension of the basic model, different components of debt are examined, pointing out that debt owed to banks and long-term debt have a stronger negative effect than other forms of debt. Comparisons with investment models estimated for other European countries suggest that the impact of debt on investment is more negative in Austria than elsewhere. Results from interaction models of debt owed to banks with an index of credit easing show that firms in industries which are more bank-dependent invest relatively more than firms in industries that are less bank-dependent after an easing of credit conditions.

This profile provides a concise and policy-relevant overview of health and the health system in Austria as part of the broader series of the State of Health in the EU country profiles. It provides a short synthesis of: the health status in the country; the determinants of health, focussing on behavioural risk factors; the organisation of the health system; and the effectiveness, accessibility and resilience of the health system. This edition has a special focus on the impact of COVID‑19. This profile is the joint work of the OECD and the European Observatory on Health Systems and Policies, in co-operation with the European Commission.

Austria is in the process of developing and implementing a comprehensive education monitoring system that is in line with the goals of the 2017 Education Reform Act. This Policy Perspective presents the final output of this two-year collaboration between the Austrian Federal Ministry of Education, Science and Research, the European Commission and the OECD. The overall goal of this project is to support the Austrian Government in the design and implementation of a new education monitoring system that balances traditional top-down implementation processes with more bottom-up approaches that leave room for co-construction and local adaptation. This report issues a set of recommendations for the monitoring system to provide data to support quality assurance, school self-evaluation, effective governance, evidence-based policy making, and allocation and use of resources. This report can be of help for any country looking to support policy development and improvement in the education system through data-informed decision-making.

Enterprises are a key provider of education and training for adults across OECD countries. Yet, policy-makers lack a detailed understanding of how training in enterprises takes place. This report opens the black box of training and informal learning in enterprises by providing in-depth insights on: i) what training and learning opportunities enterprises provide; ii) why they provide training (or not); and iii) how they make decisions about training. It presents new evidence from 100 qualitative cases studies in five countries: Austria, Estonia, France, Ireland and Italy. The findings will assist governments and social partners in designing and implementing better policies in support of training in enterprises.

This paper compares the learning gain over one year of schooling among 15-year-old students in Austria and Scotland (United Kingdom). Common metrics for reading, mathematics and science learning, as established by the Programme for International Student Assessment (PISA), are used. In order to overcome the limitations of a cross-sectional, single-cohort design, multiple cycles of PISA data are combined. The fact that Austria and Scotland moved their testing period across cycles is also exploited. The results are used to establish a benchmark for other performance differences observed in PISA, such as gender gaps, socio-economic gaps or between-country differences.